Non-Causal Observation of Viability and Identity in Long-Horizon Adaptive Systems
Abstract
This work establishes prior art for a fundamental architectural problem in long-horizon adaptive systems: the absence of a non-causal observational perspective on viability and identity continuity. The paper argues that many real-world failures of adaptive, autonomous, and learning systems do not arise from incorrect actions, violated constraints, or unstable optimization, but from gradual structural degradation and erosion of organizational identity that unfold over extended temporal horizons. Existing control, safety, and learning frameworks predominantly regulate behavior through causal mechanisms embedded in action selection, optimization objectives, or policy adaptation. As a result, observation of degradation becomes entangled with control, leading either to behavioral distortion or to silent failure modes. This work conceptualizes viability and identity continuity as global, temporally extended properties of system organization that cannot be reliably assessed from within an agent’s decision-making process without altering behavior. It identifies and formalizes the architectural consequences of causal entanglement between observation and control, including metric optimization, feedback amplification, and undetected long-horizon degradation. No mechanisms, algorithms, or implementation details are disclosed. The contribution is intentionally non-algorithmic and non-operational. Its purpose is to delineate a previously under-articulated problem space and to establish the architectural necessity of a non-causal observational dimension for long-horizon adaptive systems. This research is conducted within the broader context of the Petronus Project, alongside other conceptual and architectural layers addressing long-horizon viability, intervention cost, and regime admissibility. The present work serves as foundational prior art, defining the conceptual boundary between action-centric regulation and non-causal observation of structural viability and identity continuity.
Fields of Study & Subjects
Systems Engineering Methodologies and Applications
Infrastructure Resilience and Vulnerability Analysis
Reinforcement Learning in Robotics
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 8 January 2026
- Language
- EN
- Document type
- Preprint